Differential genotype dependent inhibition of CYP2C9 in humans

CYP2C9, CYP3A and CYP2C19 metabolize Δ9-tetrahydrocannabinol to multiple metabolites but metabolism is affected by human liver fatty acid binding protein (FABP1)

Δ9-tetrahydrocannabinol (THC) is the psychoactive constituent of cannabis. It is cleared predominantly via metabolism. Metabolism to 11-OH-THC by cytochrome P450 (CYP) 2C9 has been proposed as the main clearance pathway of THC, with the estimated fraction metabolized (fm) about 70%. The remaining clearance pathways are not well established, and it is unknown how THC is eliminated in individuals with reduced CYP2C9 activity. The goal of this study was to systematically identify the CYP enzymes contributing to THC clearance and characterize the metabolites formed. Further, this study aimed to characterize the impact of liver fatty acid binding protein (FABP1) on THC metabolism by human CYPs. THC was metabolized to at least four different metabolites including 11-OH-THC in human liver microsomes (HLMs) and with recombinant CYPs. 11-OH-THC was formed by recombinant CYP2C9 (Km,u = 0.77 nM, kcat = 12 min-1) and by recombinant CYP2C19 (Km,u = 2.2 nM, kcat = 14 min-1). The other three major metabolites were likely hydroxylations in the cyclohexenyl ring and were formed mainly by recombinant CYP3A4/5 (Km,u > 10 nM). HLM experiments confirmed the contributions of CYP2C9, CYP2C19 and CYP3A to THC metabolism. The presence of FABP1 and THC binding to FABP1 altered THC metabolism by recombinant CYPs and HLMs in an enzyme and metabolite specific manner. This suggests that FABP1 may interact with CYP enzymes and alter the fm by CYPs towards THC metabolism. In conclusion, this study is the first to systematically establish the metabolic profile of THC by human CYPs and characterize how FABP1 binding alters CYP mediated THC metabolism.

Metabolite Measurement in Index Substrate Drug Interaction Studies: A Review of the Literature and Recent New Drug Application Reviews

BACKGROUND/OBJECTIVES

Index substrates are used to understand the processes involved in pharmacokinetic (PK) drug-drug interactions (DDIs). The aim of this analysis is to review metabolite measurement in clinical DDI studies, focusing on index substrates for cytochrome P450 (CYP) enzymes, including CYP1A2 (caffeine), CYP2B6 (bupropion), CYP2C8 (repaglinide), CYP2C9 ((S)-warfarin, flurbiprofen), CYP2C19 (omeprazole), CYP2D6 (desipramine, dextromethorphan, nebivolol), and CYP3A (midazolam, triazolam).

METHODS

All data used in this evaluation were obtained from the Certara Drug Interaction Database. Clinical index substrate DDI studies with PK data for at least one metabolite, available from literature and recent new drug application reviews, were reviewed. Further, for positive DDI studies, a correlation analysis was performed between changes in plasma exposure of index substrates and their marker metabolites.

RESULTS

A total of 3261 individual index DDI studies were available, with 45% measuring at least one metabolite. The occurrence of metabolite measurement in clinical DDI studies varied widely between index substrates and enzymes.

DISCUSSION AND CONCLUSIONS

For substrates such as caffeine, bupropion, omeprazole, and dextromethorphan, the use of the metabolite/parent area under the curve ratio can provide greater sensitivity to DDI or reduce intrasubject variability. In some cases (e.g., omeprazole, repaglinide), the inclusion of metabolite measurement can provide mechanistic insights to understand complex interactions.

A Physiological-Based Pharmacokinetic Model Embedded with a Target-Mediated Drug Disposition Mechanism Can Characterize Single-Dose Warfarin Pharmacokinetic Profiles in Subjects with Various CYP2C9 Genotypes under Different Cotreatments

Warfarin, a commonly prescribed oral anticoagulant medication, is highly effective in treating deep vein thrombosis and pulmonary embolism. However, the clinical dosing of warfarin is complicated by high interindividual variability in drug exposure and response and its narrow therapeutic index. CYP2C9 genetic polymorphism and drug-drug interactions (DDIs) are substantial contributors to this high variability of warfarin pharmacokinetics (PK), among numerous factors. Building a physiology-based pharmacokinetic (PBPK) model for warfarin is not only critical for a mechanistic characterization of warfarin PK but also useful for investigating the complicated dose-exposure relationship of warfarin. Thus, the objective of this study was to develop a PBPK model for warfarin that integrates information regarding CYP2C9 genetic polymorphisms and their impact on DDIs. Generic PBPK models for both S- and R-warfarin, the two enantiomers of warfarin, were constructed in R with the mrgsolve package. As expected, a generic PBPK model structure did not adequately characterize the warfarin PK profile collected up to 15 days following the administration of a single oral dose of warfarin, especially for S-warfarin. However, following the integration of an empirical target-mediated drug disposition (TMDD) component, the PBPK-TMDD model well characterized the PK profiles collected for both S- and R-warfarin in subjects with different CYP2C9 genotypes. Following the integration of enzyme inhibition and induction effects, the PBPK-TMDD model also characterized the PK profiles of both S- and R-warfarin in various DDI settings. The developed mathematic framework may be useful in building algorithms to better inform the clinical dosing of warfarin. SIGNIFICANCE STATEMENT: The present study found that a traditional physiology-based pharmacokinetic (PBPK) model cannot sufficiently characterize the pharmacokinetic profiles of warfarin enantiomers when warfarin is administered as a single dose, but a PBPK model with a target-mediated drug disposition mechanism can. After incorporating CYP2C9 genotypes and drug-drug interaction information, the developed model is anticipated to facilitate the understanding of warfarin disposition in subjects with different CYP2C9 genotypes in the absence and presence of both cytochrome P450 inhibitors and cytochrome P450 inducers.

Physiologically based pharmacokinetic (PBPK) modeling of flurbiprofen in different CYP2C9 genotypes

The aim of this study was to establish the physiologically based pharmacokinetic (PBPK) model of flurbiprofen related to CYP2C9 genetic polymorphism and describe the pharmacokinetics of flurbiprofen in different CYP2C9 genotypes. PK-Sim® software was used for the model development and validation. A total of 16 clinical pharmacokinetic data for flurbiprofen in different CYP2C9 genotypes, dose regimens, and age groups were used for the PBPK modeling. Turnover number (k_cat) of CYP2C9 values were optimized to capture the observed profiles in different CYP2C9 genotypes. In the simulation, predicted fraction metabolized by CYP2C9, fraction excreted to urine, bioavailability, and volume of distribution were similar to previously reported values. Predicted plasma concentration-time profiles in different CYP2C9 genotypes were visually similar to the observed profiles. Predicted AUC_inf in CYP2C9*1/*2, CYP2C9*1/*3, and CYP2C9*3/*3 genotypes were 1.44-, 2.05-, and 3.67-fold higher than the CYP2C9*1/*1 genotype. The ranges of fold errors for AUC_inf, C_max, and t_1/2 were 0.84-1.00, 0.61-1.22, and 0.74-0.94 in development and 0.59-0.98, 0.52-0.97, and 0.61-1.52 in validation, respectively, which were within the acceptance criterion. Thus, the PBPK model was successfully established and described the pharmacokinetics of flurbiprofen in different CYP2C9 genotypes, dose regimens, and age groups. The present model could guide the decision-making of tailored drug administration strategy by predicting the pharmacokinetics of flurbiprofen in various clinical scenarios.

Physiologically based pharmacokinetic modeling of candesartan related to CYP2C9 genetic polymorphism in adult and pediatric patients

Candesartan cilexetil is an angiotensin II receptor blocker and it is widely used to treat hypertension and heart failure. This drug is a prodrug that rapidly converts to candesartan after oral administration. Candesartan is metabolized by cytochrome P450 2C9 (CYP2C9) enzyme or uridine diphosphate glucurinosyltransferase 1A3, or excreted in an unchanged form through urine, biliary tract and feces. We investigated the effect of genetic polymorphism of CYP2C9 enzyme on drug pharmacokinetics using physiologically based pharmacokinetic (PBPK) modeling. In addition, by introducing the age and ethnicity into the model, we developed a model that can propose an appropriate dosage regimen taking into account the individual characteristics of each patient. To evaluate the suitability of the model, the results of a clinical trial on twenty-two healthy Korean subjects and their CYP2C9 genetic polymorphism data was applied. In this study, PK-Sim® was used to develop the PBPK model of candesartan.

Physiologically Based Pharmacokinetic/Pharmacodynamic Modeling to Predict the Impact of CYP2C9 Genetic Polymorphisms, Co-Medication and Formulation on the Pharmacokinetics and Pharmacodynamics of Flurbiprofen

Physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) models can serve as a powerful framework for predicting the influence as well as the interaction of formulation, genetic polymorphism and co-medication on the pharmacokinetics and pharmacodynamics of drug substances. In this study, flurbiprofen, a potent non-steroid anti-inflammatory drug, was chosen as a model drug. Flurbiprofen has absolute bioavailability of ~95% and linear pharmacokinetics in the dose range of 50–300 mg. Its absorption is considered variable and complex, often associated with double peak phenomena, and its pharmacokinetics are characterized by high inter-subject variability, mainly due to its metabolism by the polymorphic CYP2C9 (fmCYP2C9 ≥ 0.71). In this study, by leveraging in vitro, in silico and in vivo data, an integrated PBPK/PD model with mechanistic absorption was developed and evaluated against clinical data from PK, PD, drug-drug and gene-drug interaction studies. The PBPK model successfully predicted (within 2-fold) 36 out of 38 observed concentration-time profiles of flurbiprofen as well as the CYP2C9 genetic effects after administration of different intravenous and oral dosage forms over a dose range of 40–300 mg in both Caucasian and Chinese healthy volunteers. All model predictions for C_max, AUC_inf and CL/F were within two-fold of their respective mean or geometric mean values, while 90% of the predictions of C_max, 81% of the predictions of AUC_inf and 74% of the predictions of Cl/F were within 1.25 fold. In addition, the drug-drug and drug-gene interactions were predicted within 1.5-fold of the observed interaction ratios (AUC, C_max ratios). The validated PBPK model was further expanded by linking it to an inhibitory E_max model describing the analgesic efficacy of flurbiprofen and applying it to explore the effect of formulation and genetic polymorphisms on the onset and duration of pain relief. This comprehensive PBPK/PD analysis, along with a detailed translational biopharmaceutic framework including appropriately designed biorelevant in vitro experiments and in vitro-in vivo extrapolation, provided mechanistic insight on the impact of formulation and genetic variations, two major determinants of the population variability, on the PK/PD of flurbiprofen. Clinically relevant specifications and potential dose adjustments were also proposed. Overall, the present work highlights the value of a translational PBPK/PD approach, tailored to target populations and genotypes, as an approach towards achieving personalized medicine.

Phenoconversion of Cytochrome P450 Metabolism: A Systematic Review

Phenoconversion is the mismatch between the individual’s genotype-based prediction of drug metabolism and the true capacity to metabolize drugs due to nongenetic factors. While the concept of phenoconversion has been described in narrative reviews, no systematic review is available. A systematic review was conducted to investigate factors contributing to phenoconversion and the impact on cytochrome P450 metabolism. Twenty-seven studies met the inclusion criteria and were incorporated in this review, of which 14 demonstrate phenoconversion for a specific genotype group. Phenoconversion into a lower metabolizer phenotype was reported for concomitant use of CYP450-inhibiting drugs, increasing age, cancer, and inflammation. Phenoconversion into a higher metabolizer phenotype was reported for concomitant use of CYP450 inducers and smoking. Moreover, alcohol, pregnancy, and vitamin D exposure are factors where study data suggested phenoconversion. The studies reported genotype–phenotype discrepancies, but the impact of phenoconversion on the effectiveness and toxicity in the clinical setting remains unclear. In conclusion, phenoconversion is caused by both extrinsic factors and patient- and disease-related factors. The mechanism(s) behind and the extent to which CYP450 metabolism is affected remain unexplored. If studied more comprehensively, accounting for phenoconversion may help to improve our ability to predict the individual CYP450 metabolism and personalize drug treatment.

Optimising Seniors' Metabolism of Medications and Avoiding Adverse Drug Events Using Data on How Metabolism by Their P450 Enzymes Varies with Ancestry and Drug-Drug and Drug-Drug-Gene Interactions

Many individuals ≥65 have multiple illnesses and polypharmacy. Primary care physicians prescribe >70% of their medications and renew specialists’ prescriptions. Seventy-five percent of all medications are metabolised by P450 cytochrome enzymes. This article provides unique detailed tables how to avoid adverse drug events and optimise prescribing based on two key databases. DrugBank is a detailed database of 13,000 medications and both the P450 and other complex pathways that metabolise them. The Flockhart Tables are detailed lists of the P450 enzymes and also include all the medications which inhibit or induce metabolism by P450 cytochrome enzymes, which can result in undertreatment, overtreatment, or potentially toxic levels. Humans have used medications for a few decades and these enzymes have not been subject to evolutionary pressure. Thus, there is enormous variation in enzymatic functioning and by ancestry. Differences for ancestry groups in genetic metabolism based on a worldwide meta-analysis are discussed and this article provides advice how to prescribe for individuals of different ancestry. Prescribing advice from two key organisations, the Dutch Pharmacogenetics Working Group and the Clinical Pharmacogenetics Implementation Consortium is summarised. Currently, detailed pharmacogenomic advice is only available in some specialist clinics in major hospitals. However, this article provides detailed pharmacogenomic advice for primary care and other physicians and also physicians working in rural and remote areas worldwide. Physicians could quickly search the tables for the medications they intend to prescribe.

Role of transporters in the disposition of a novel β-lactamase inhibitor: relebactam (MK-7655)

OBJECTIVES

To identify the transporters involved in renal elimination of relebactam, and to assess the potential of relebactam as a perpetrator or victim of drug-drug interactions (DDIs) for major drug transporters.

METHODS

A series of bidirectional transport, uptake and inhibition studies were conducted in vitro using transfected cell lines and membrane vesicles. The inhibitory effects of relebactam on major drug transporters, as well as the inhibitory effects of commonly used antibiotics/antifungals on organic anion transporter (OAT) 3-mediated uptake of relebactam, were assessed.

RESULTS

Relebactam was shown to be a substrate of OAT3, OAT4, and multidrug and toxin extrusion (MATE) proteins MATE1 and MATE2K. Relebactam did not show profound inhibition across a panel of transporters, including organic anion-transporting polypeptides 1B1 and 1B3, OAT1, OAT3, organic cation transporter 2, MATE1, MATE2K, breast cancer resistance protein, multidrug resistance protein 1 and the bile salt export pump. Among the antibiotics/antifungals assessed for potential DDIs, probenecid demonstrated the most potent in vitro inhibition of relebactam uptake; however, such in vitro data did not translate into clinically relevant DDIs, suggesting that relebactam can be co-administered with OAT inhibitors, such as probenecid.

CONCLUSIONS

Overall, relebactam has low potential to be a victim or perpetrator of DDIs with major drug transporters.

Effect of Fluconazole Coadministration and CYP2C9 Genetic Polymorphism on Siponimod Pharmacokinetics in Healthy Subjects

Objectives

The aim of this study was to assess the pharmacokinetics (PK) and safety/tolerability of siponimod in healthy subjects when coadministered with (1) the moderate cytochrome P450 (CYP) 2C9 and CYP3A inhibitor fluconazole (Study A), and (2) with three different CYP2C9 genotype variants (Study B).

Methods

Study A was an open-label, single-dose study comprising periods 1 (14 days; day 1: siponimod 4 mg) and 2 (20 days; day 1: fluconazole 200 mg twice daily; days 2–19: fluconazole 200 mg once daily; day 3: siponimod 4 mg) in healthy subjects (n = 14) with the wild-type CYP2C9 genotype (CYP2C9*1/*1). Study B was a multicentre, open-label study comprising parts 1 (day 1: siponimod 0.25 mg once daily in the CYP2C9*1/*1, CYP2C9*2/*3 and CYP2C9*3/*3 genotypes) and 2 (days 1–2: 0.25 mg once daily; day 3: 0.5 mg once daily in the CYP2C9*2/*3 and CYP2C9*3/*3 genotypes only) in healthy subjects with polymorphic variants of CYP2C9 (n = 24). Pharmacokinetic parameters were calculated using noncompartmental methods.

Results

In Study A, coadministration with fluconazole produced an approximately twofold increase in mean area under the curve (AUC) versus siponimod alone (from 1110 to 2160 h*ng/mL), and an increase in maximum plasma concentration (C_max; from 31.2 to 34.0 ng/mL) and elimination half-life (T_½; from 40.6 to 61.6 h). In Study B, the AUCs of siponimod were approximately two to fourfold greater in subjects with the CYP2C9*2/*3 and CYP2C9*3/*3 genotypes, with a minor increase in C_max versus the CYP2C9*1/*1 genotype. The mean T_½ was prolonged in the CYP2C9*2/*3 (51 h) and CYP2C9*3/*3 (126 h) genotypes versus the CYP2C9*1/*1 (28 h) genotype. Siponimod did not result in increased adverse events in healthy subjects in both studies.

Conclusions

Changes in siponimod PK, when coadministered with fluconazole at steady-state and in subjects with different CYP2C9 genotypes, indicate that the reduced CYP2C9 enzymatic activity does not affect the absorption phase of siponimod but prolongs the elimination phase. These results confirm the relevance of CYP2C9 activity on siponimod metabolism in humans.

Electronic supplementary material

The online version of this article (10.1007/s40262-018-0700-3) contains supplementary material, which is available to authorized users.

Impact of CYP2C9-Interacting Drugs on Warfarin Pharmacogenomics

Precise dosing of warfarin is important to achieve therapeutic benefit without adverse effects. Pharmacogenomics explains some interindividual variability in warfarin response, but less attention has been paid to drug‐drug interactions in the context of genetic factors. We investigated retrospectively the combined effects of cytochrome P450 (CYP)2C9 and vitamin K epoxide reductase complex (VKORC)1 genotypes and concurrent exposure to CYP2C9‐interacting drugs on long‐term measures of warfarin anticoagulation. Study participants predicted to be sensitive responders to warfarin based on CYP2C9 and VKORC1 genotypes, had significantly greater international normalized ratio (INR) variability over time. Participants who were concurrently taking CYP2C9‐interacting drugs were found to have greater INR variability and lesser time in therapeutic range. The associations of INR variability with genotype were driven by the subgroup not exposed to interacting drugs, whereas the effect of interacting drug exposure was driven by the subgroup categorized as normal responders. Our findings emphasize the importance of considering drug interactions in pharmacogenomic studies.

Genotype-sensitive reversible and time-dependent CYP2D6 inhibition in human liver microsomes

Cytochrome P450 (CYP) 2D6 metabolizes a wide range of xenobiotics and is characterized by a huge interindividual variability. A recent clinical study highlighted differential magnitude of CYP inhibition as a function of CYP2D6 genotype. The aim of this study was to investigate the effect of CYP2D6 genotype on the inhibition of dextromethorphan O-demethylation by duloxetine and paroxetine in human liver microsomes (HLMs). The study focused on genotypes defined by the combination of two fully functional alleles (activity score 2, AS 2, n = 6), of one fully functional and one reduced allele (activity score 1.5, AS 1.5, n = 4) and of one fully functional and one non-functional allele (activity score 1, AS 1, n = 6), which all predict extensive metabolizer phenotype. Kinetic experiments showed that maximal reaction velocity was affected by CYP2D6 genotype, with a decrease in 33% of V_max in AS 1 HLMs compared to AS 2 (P = 0.06). No difference in inhibition parameters K_i , K_I and k_inact was observed neither with the competitive inhibitor duloxetine nor with the time-dependent inhibitor paroxetine. Among the genotypes tested, we found no difference in absolute CYP2D6 microsomal levels with ELISA immunoquantification. Therefore, our results suggest that genotype-sensitive magnitude of drug-drug interactions recently observed in vivo is likely to be due to differential amounts of functional enzymes at the microsomal level rather than to a difference in inhibition potencies across genotypes, which motivates for further quantitative proteomic investigations of functional and variant CYP2D6 alleles.

Complex Drug-Drug-Gene-Disease Interactions Involving Cytochromes P450: Systematic Review of Published Case Reports and Clinical Perspectives

Drug pharmacokinetics (PK) is influenced by multiple intrinsic and extrinsic factors, among which concomitant medications are responsible for drug-drug interactions (DDIs) that may have a clinical relevance, resulting in adverse drug reactions or reduced efficacy. The addition of intrinsic factors affecting cytochromes P450 (CYPs) activity and/or expression, such as genetic polymorphisms and diseases, may potentiate the impact and clinical relevance of DDIs. In addition, greater variability in drug levels and exposures has been observed when such intrinsic factors are present in addition to concomitant medications perpetrating DDIs. This variability results in poor predictability of DDIs and potentially dramatic clinical consequences. The present review illustrates the issue of complex DDIs using systematically searched published case reports of DDIs involving genetic polymorphisms, renal impairment, cirrhosis, and/or inflammation. Current knowledge on the impact of each of these factors on drug exposure and DDIs is summarized and future perspectives for the management of such complex DDIs in clinical practice are discussed, including the use of advanced Computerized Physician Order Entry (CPOE) systems, the development of model-based dose optimization strategies, and the education of healthcare professionals with respect to personalized medicine.

The Clinical Pharmacokinetics and Pharmacodynamics of Warfarin When Combined with Compound Danshen: A Case Study for Combined Treatment of Coronary Heart Diseases with Atrial Fibrillation

Warfarin is used as anticoagulant and Compound Danshen prescription (CDP) is able to promote blood circulation. The combination might produce a synergic effect for patients of coronary heart diseases (CHDs) with atrial fibrillation (AF). Whether the combination increases the bleeding risk of warfarin is unclear, so the effects of Compound Danshen dripping pill (CDDP) on the pharmacokinetics (PK) and pharmacodynamics (PD) profiles of warfarin was investigated in patients. The dose and blood concentrations of warfarin, the four indicators of blood coagulation, prothrombin time, activated partial thromboplatin time, thrombin time, fibrinogen, and international normalized ratio value were compared when with and without CDDP treatment. The population PK (PPK) and PPK-PD models were established to assess patient demographics, genetic polymorphisms and CDDP as covariates. And the Seattle Angina Questionnaire was used to evaluate clinical efficacy, and the bleeding risk of combination was analyzed. The results indicated that CDDP had little influence on PK and PD profiles of warfarin in most patients and the combination of CCDP and warfarin would be a promising alternative regime for CHD with AF patients. The study was registered on China Clinical Trial Registry with number ChiCTR-ONRC-13003523.

Pharmacogenetics of drug-drug interaction and drug-drug-gene interaction: a systematic review on CYP2C9, CYP2C19 and CYP2D6

Currently, most guidelines on drug-drug interaction (DDI) neither consider the potential effect of genetic polymorphism in the strength of the interaction nor do they account for the complex interaction caused by the combination of DDI and drug-gene interaction (DGI) where there are multiple biotransformation pathways, which is referred to as drug-drug-gene interaction (DDGI). In this systematic review, we report the impact of pharmacogenetics on DDI and DDGI in which three major drug-metabolizing enzymes - CYP2C9, CYP2C19 and CYP2D6 - are central. We observed that several DDI and DDGI are highly gene-dependent, leading to a different magnitude of interaction. Precision drug therapy should take pharmacogenetics into account when drug interactions in clinical practice are expected.

Pharmacogenomics of the cytochrome P450 2C family: impacts of amino acid variations on drug metabolism

Pharmacogenomics investigates DNA and RNA variations in the human genome related to drug responses. Cytochrome P450 (CYP) is a supergene family of drug-metabolizing enzymes responsible for the metabolism of approximately 90% of human drugs. Among the major CYP isoforms, the CYP2C subfamily is of clinical significance because it metabolizes approximately 20% of clinically administrated drugs and represents several variant alleles leading to adverse drug reactions or altering drug efficacy. Here, we review recent progress on understanding the interindividual variability of the CYP2C members and the functional and clinical impact on drug metabolism. We summarize current advances in the molecular modeling of CYP2C polymorphisms and discuss the structural bases and molecular mechanisms of amino acid variants of CYP2C members that affect drug metabolism.

The Effect of Genetic Polymorphism on the Inhibition of Azole Antifungal Agents Against CYP2C9-Mediated Metabolism

We investigated the effect of cytochrome P450 (CYP) 2C9 polymorphism on the inhibition of methylhydroxylation activity of tolbutamide, a typical CYP2C9 substrate, by triazole antifungal agents, fluconazole and voriconazole. Although the Michaelis constants (Km), maximal velocities (Vmax), and Vmax/Km values for CYP2C9.1 (wild type) and CYP2C9.2 (Arg144Cys) were similar and CYP2C9.3 (Ile359Leu) had a higher Km and a lower Vmax than CYP2C9.1 and CYP2C9.2, the inhibition constants of fluconazole and voriconazole against CYP2C9.2 were lower than that against CYP2C9.1 and CYP2C9.3. These results suggest that more careful administration of azole antifungals to patients with the CYP2C9*2 allele might be required because of the strong inhibitory effects.

Addressing phenoconversion: the Achilles' heel of personalized medicine

Phenoconversion is a phenomenon that converts genotypic extensive metabolizers (EMs) into phenotypic poor metabolizers (PMs) of drugs, thereby modifying their clinical response to that of genotypic PMs. Phenoconversion, usually resulting from nongenetic extrinsic factors, has a significant impact on the analysis and interpretation of genotype-focused clinical outcome association studies and personalizing therapy in routine clinical practice. The high phenotypic variability or genotype-phenotype mismatch, frequently observed due to phenoconversion within the genotypic EM population, means that the real number of phenotypic PM subjects may be greater than predicted from their genotype alone, because many genotypic EMs would be phenotypically PMs. If the phenoconverted population with genotype-phenotype mismatch, most extensively studied for CYP2D6, is as large as the evidence suggests, there is a real risk that genotype-focused association studies, typically correlating only the genotype with clinical outcomes, may miss clinically strong pharmacogenetic associations, thus compromising any potential for advancing the prospects of personalized medicine. This review focuses primarily on co-medication-induced phenoconversion and discusses potential approaches to rectify some of the current shortcomings. It advocates routine phenotyping of subjects in genotype-focused association studies and proposes a new nomenclature to categorize study populations. Even with strong and reliable data associating patients' genotypes with clinical outcome(s), there are problems clinically in applying this knowledge into routine pharmacotherapy because of potential genotype-phenotype mismatch. Drug-induced phenoconversion during routine clinical practice remains a major public health issue. Therefore, the principal challenges facing personalized medicine, which need to be addressed, include identification of the following factors: (i) drugs that are susceptible to phenoconversion; (ii) co-medications that can cause phenoconversion; and (iii) dosage amendments that need to be applied during and following phenoconversion.

Reaction phenotyping: advances in the experimental strategies used to characterize the contribution of drug-metabolizing enzymes

During the process of drug discovery, the pharmaceutical industry is faced with numerous challenges. One challenge is the successful prediction of the major routes of human clearance of new medications. For compounds cleared by metabolism, accurate predictions help provide an early risk assessment of their potential to exhibit significant interpatient differences in pharmacokinetics via routes of metabolism catalyzed by functionally polymorphic enzymes and/or clinically significant metabolic drug-drug interactions. This review details the most recent and emerging in vitro strategies used by drug metabolism and pharmacokinetic scientists to better determine rates and routes of metabolic clearance and how to translate these parameters to estimate the amount these routes contribute to overall clearance, commonly referred to as fraction metabolized. The enzymes covered in this review include cytochrome P450s together with other enzymatic pathways whose involvement in metabolic clearance has become increasingly important as efforts to mitigate cytochrome P450 clearance are successful. Advances in the prediction of the fraction metabolized include newly developed methods to differentiate CYP3A4 from the polymorphic enzyme CYP3A5, scaling tools for UDP-glucuronosyltranferase, and estimation of fraction metabolized for substrates of aldehyde oxidase.

CYP2C9 and ABCG2 polymorphisms as risk factors for developing adverse drug reactions in renal transplant patients taking fluvastatin: a case-control study

AIM

To investigate whether an association exists between fluvastatin-induced adverse drug reactions (ADRs) and polymorphisms in genes encoding the metabolizing enzyme CYP2C9 and the drug transporter ABCG2 in renal transplant recipients (RTRs).

MATERIALS & METHODS

Fifty-two RTRs that experienced fluvastatin ADRs and 52 controls matched for age, gender, dose of fluvastatin and immunosuppressive use were enrolled in the study. Genotyping for CYP2C9*2, *3 and ABCG2 421C>A variants was performed by real-time PCR.

RESULTS

CYP2C9 homozygous and heterozygous mutant allele (*2 or *3) carriers had 2.5-times greater odds of developing adverse effects (χ² = 4.370; degrees of freedom = 1; p = 0.037; φ = 0.21, odds ratio [OR]: 2.44; 95% CI: 1.05-5.71). Patients who were the carriers of at least one mutant CYP2C9 allele (*2 or *3) and who were receiving CYP2C9 inhibitors, had more than six-times greater odds of having adverse effects than those without the inhibitor included in their therapy (p = 0.027; OR: 6.59; 95% CI: 1.24-35.08). Patients with ABCG2 421CA or AA (taken together) had almost four-times greater odds of developing adverse effects than those with ABCG2 421CC genotype (χ² = 6.190; degrees of freedom = 1; p = 0.013; φ = 0.24, OR: 3.81; 95% CI: 1.27-11.45). Patients with A allele had 2.75-times (95% CI: 1.02-7.40) greater odds of developing adverse effects than those with C allele.

CONCLUSION

Our preliminary data demonstrate an association between fluvastatin-induced ADRs in RTRs and genetic variants in the CYP2C9 and ABCG2 genes.

Inhibition of baicalin on metabolism of phenacetin, a probe of CYP1A2, in human liver microsomes and in rats

Baicalin has been used as mainly bioactive constituent of about 100 kinds of traditional Chinese medicines in Chinese pharmacopoeia. The effect of baicalin on cytochrome P450 should be paid more attention because baicalin was used widely. The aim of this study was to investigate whether baicalin could inhibit CYP1A2 in pooled human liver microsomes (HLMs) and in rats in vivo and the gene polymorphisms could affect inter-individual variation in IC50 in 28 human livers. Phenacetin was used as probe of CYP1A2. Kinetic parameter of CYP1A2 and IC50 of baicalin on CYP1A2 to each sample were measured and the common CYP1A2 polymorphisms (-3860G>A and -163C>A) were genotyped. The results showed that baicalin exhibited a mixed-type inhibition in pooled HLMs, with a Ki value of 25.4 µM. There was substantial variation in Km, Vmax, CLint of CYP1A2 and IC50 of baicalin on CYP1A2 (3∼10-fold). The range was from 26.6 to 114.8 µM for Km, from 333 to 1330 pmol·min(-1)·mg(-1)protein for Vmax and from 3.8 to 45.3 µL·min(-1)·mg(-1) protein for CLint in HLMs (n = 28). The Mean (range) value of IC50 in 28 HLMs was 36.3 (18.9 to 56.1) µM. The genotypes of -3860G>A and -163C>A had no significant effect on the inhibition of baicalin on CYP1A2. The animal experiment results showed that baicalin (450 mg/kg, i.v.) significantly decreased the Cmax and CL of phenacetin, and increased C(60 min), t1/2, Vd and AUC (P<0.05). There were significant correlations between percentage of control in C(60 min), t1/2, CL, AUC of phenacetin and Cmax of baicalin in 11 rats (P<0.05). Protein binding experiments in vitro showed that baicalin (0-2000 mg/L) increased the unbound phenacetin from 14.5% to 28.3%. In conclusion, baicalin can inhibit the activity of CYP1A2 in HLMs and exhibit large inter-individual variation that has no relationship with gene polymorphism. Baicalin can change the pharmacokinetics of phenacetin in rats.

Characterization of inhibition kinetics of (S)-warfarin hydroxylation by noscapine: implications in warfarin therapy

Noscapine is an antitussive and potential anticancer drug. Clinically significant interactions between warfarin and noscapine have been previously reported. In this study, to provide a basis for warfarin dosage adjustment, the inhibition kinetics of noscapine against warfarin metabolism was characterized. Our enzyme kinetics data obtained from human liver microsomes and recombinant CYP2C9 proteins indicate that noscapine is a competitive inhibitor of the (S)-warfarin 7-hydroxylation reaction by CYP2C9. Interestingly, noscapine also inhibited (S)-warfarin metabolism in a NADPH- and time-dependent manner, and removal of unbound noscapine and its metabolites by ultrafiltration did not reverse inhibition of (S)-warfarin metabolism by noscapine, suggesting mechanism-based inhibition of CYP2C9 by noscapine. Spectral scanning of the reaction between CYP2C9 and noscapine revealed the formation of an absorption spectrum at 458 nm, indicating the formation of a metabolite-intermediate complex. Surprisingly, noscapine is a 2- to 3-fold more efficient inactivator of CYP2C9.2 and CYP2C9.3 variants than it is of the wild type, by unknown mechanisms. Based on the inhibitory kinetic data, (S)-warfarin exposure is predicted to increase up to 7-fold (depending on CYP2C9 genotypes) upon noscapine coadministration, mainly due to mechanism-based inactivation of CYP2C9 by noscapine. Together, these results indicate that mechanism-based inhibition of CYP2C9 by noscapine may dramatically alter pharmacokinetics of warfarin and provide a basis for warfarin dosage adjustment when noscapine is coadministered.

Impact of genetic polymorphism on drug-drug interactions mediated by cytochromes: a general approach

Currently, quantitative prediction of the impact of genetic polymorphism and drug-drug interactions mediated by cytochromes, based on in vivo data, is made by two separate methods and restricted to a single cytochrome. We propose a unified approach for describing the combined impact of drug-drug interactions and genetic polymorphism on drug exposure. It relies on in vivo data and uses the following three characteristic parameters: one for the victim drug, one for the interacting drug, and another for the genotype. These parameters are known for a wide range of drugs and genotypes. The metrics of interest are the ratio of victim drug area under the curve (AUC) in patients with genetic variants taking both drugs, to the AUC in patients with either variant or wild-type genotype taking the victim drug alone. The approach was evaluated by external validation, comparing predicted and observed AUC ratios found in the literature. Data were found for 22 substrates, 30 interacting drugs, and 38 substrate-interacting drug couples. The mean prediction error of AUC ratios was 0.02, and the mean prediction absolute error was 0.38 and 1.34, respectively. The model may be used to predict the variations in exposure resulting from a number of drug-drug-genotype combinations. The proposed approach will help (1) to identify comedications and population at risk, (2) to adapt dosing regimens, and (3) to prioritize the clinical pharmacokinetic studies to be done.

Impact of genetic polymorphisms in CYP2C9 and CYP2C19 on the pharmacokinetics of clinically used drugs

Human cytochrome P450 (CYP) is a superfamily of hemoproteins which oxidize a number of endogenous compounds and xenobiotics. The human CYP2C subfamily consists of four members: CYP2C8, CYP2C9, CYP2C18 and CYP2C19. CYP2C9 and CYP2C19 are important drug-metabolizing enzymes and together metabolize approximately 20% of therapeutically used drugs. Forty-two allelic variants for CYP2C9 and 34 for CYP2C19 have been reported. The frequencies of these variants show marked inter-ethnic variation. The functional consequences of genetic polymorphisms have been examined, and many studies have shown the clinical importance of these polymorphisms. Current evidence suggests that taking the genetically determined metabolic capacity of CYP2C9 and CYP2C19 into account has the potential to improve individual risk/benefit relationships. However, more prospective studies with clinical endpoints are needed before the paradigm of "personalized medicine" based on the variants can be established. This review summarizes the currently available important information on this topic.

A clinically significant interaction between warfarin and simvastatin is unique to carriers of the CYP2C9*3 allele

Background: Simvastatin interacts with warfarin, but the strength of the interaction varies between individual patients, indicating a genetic predisposition. Patients & methods: The influence of the CYP2C9*2 and CYP2C9*3 polymorphisms on the interaction between simvastatin and warfarin was analyzed in data from 1132 patients. Results: Simvastatin use reduced warfarin dose requirements by 29% in carriers of the CYP2C9*3 allele, compared with 5% in noncarriers. A regression model showed a significant influence of CYP2C9*3 on the drug–drug interaction, predicting a warfarin dose reduction of 25% in CYP2C9*3 heterozygotes and 43% in CYP2C9*3 homozygotes. Conclusion: Our data indicate that the CYP2C9*3 polymorphism predisposes for a pharmacologic interaction between warfarin and simvastatin.

Original submitted 5 January 2012; Revision submitted 15 February 2012

Development of an in vitro system with human liver microsomes for phenotyping of CYP2C9 genetic polymorphisms with a mechanism-based inactivator

Polymorphisms in cytochrome P450 enzymes can significantly alter the rate of drug metabolism, as well as the extent of drug-drug interactions. Individuals who homozygotically express the CYP2C9*3 allele (I359L) of CYP2C9 exhibit ∼70 to 80% reductions in the oral clearance of drugs metabolized through this pathway; the reduction in clearance is ∼40 to 50% for heterozygotic individuals. Although these polymorphisms result in a decrease in the activity of individual enzyme molecules, we hypothesized that decreasing the total number of active enzyme molecules in an in vitro system (CYP2C9*1/*1 human liver microsomes) by an equivalent percentage could produce the same net change in overall metabolic capacity. To this end, the selective CYP2C9 mechanism-based inactivator tienilic acid was used to reduce irreversibly the total CYP2C9 activity in human liver microsomes. Tienilic acid concentrations were effectively titrated to produce microsomal preparations with 43 and 73% less activity, mimicking the CYP2C9*1/*3 and CYP2C9*3/*3 genotypes, respectively. With probe substrates specific for other major cytochrome P450 enzymes (CYP1A2, CYP2B6, CYP2C8, CYP2C19, CYP2D6, CYP2E1, and CYP3A4), no apparent changes in the rate of metabolism were noted for these enzymes after the addition of tienilic acid, which suggests that this model is selective for CYP2C9. In lieu of using rare human liver microsomes from CYP2C9*1/*3 and CYP2C9*3/*3 individuals, a tienilic acid-created knockdown in human liver microsomes may be an appropriate in vitro model to determine CYP2C9-mediated metabolism of a given substrate, to determine whether other drug-metabolizing enzymes may compensate for reduced CYP2C9 activity, and to predict the extent of genotype-dependent drug-drug interactions.

Evaluation of the effects of cytochrome P450 nonsynonymous single-nucleotide polymorphisms on tanshinol borneol ester metabolism and inhibition potential

Nonsynonymous single-nucleotide polymorphisms (nsSNPs) in cytochrome P450 (P450) genes may affect drug metabolism and drug-drug interactions (DDIs), potentially leading to adverse drug reactions. Functional characterization of the nsSNPs in P450 genes is important to help us understand the impact of genetic factors on P450-mediated drug metabolism and DDIs. To evaluate the effects of P450 nsSNPs on the metabolism and inhibition potential of a candidate drug, tanshinol borneol ester (DBZ), we obtained and experimentally validated eight yeast-expressed human P450 isoforms and their nsSNP variants and tested DBZ using these recombinant P450 enzymes. The results suggested that CYP2C8 is the major enzyme responsible for DBZ metabolism. In addition, compared with prototypic CYP2C8, the allelic variant, CYP2C8.3, produced a 54% decrease in the intrinsic clearance of DBZ. The inhibitory potency of DBZ toward CYP3A4 was greater than that toward other P450 isoforms, including CYP1A2, CYP2C8, CYP2C9, CYP2C19, and CYP2D6. Moreover, the inhibitory potency toward three CYP3A4 allelic variants, CYP3A4.2, CYP3A4.12, and CYP3A4.16, was reduced 2- to 10-fold relative to prototype CYP3A4. These results provide useful information for understanding the influence of P450 genetic polymorphisms on DBZ metabolism and may help to design future clinical trials of DBZ. Our results suggest applications for in vitro P450 assays both for basic research in pharmacogenomics and for drug development.

Role of biotransformation in drug-induced toxicity: influence of intra- and inter-species differences in drug metabolism

It is now widely appreciated that drug metabolites, in addition to the parent drugs themselves, can mediate the serious adverse effects exhibited by some new therapeutic agents, and as a result, there has been heightened interest in the field of drug metabolism from researchers in academia, the pharmaceutical industry, and regulatory agencies. Much progress has been made in recent years in understanding mechanisms of toxicities caused by drug metabolites, and in understanding the numerous factors that influence individual exposure to products of drug biotransformation. This review addresses some of these factors, including the role of drug-drug interactions, reactive metabolite formation, individual susceptibility, and species differences in drug disposition caused by genetic polymorphisms in drug-metabolizing enzymes. Examples are provided of adverse reactions that are linked to drug metabolism, and the mechanisms underlying variability in toxic response are discussed. Finally, some future directions for research in this field are highlighted in the context of the discovery and development of new therapeutic agents.

Relative impact of genotype and enzyme induction on the metabolic capacity of CYP2C9 in healthy volunteers

Pharmacokinetics in individual subjects is determined by genes and environment. The relative contributions of enzyme induction and inherited genomic variation to cytochrome P450 enzyme 2C9 (CYP2C9) activity are unknown. In 130 volunteers, CYP2C9 activity was measured in vivo using tolbutamide as a probe drug. Tolbutamide was administered orally, and the pharmacokinetics of the drug was analyzed twice--before and after four doses of 450 mg rifampin. Mean total apparent clearances (Cl/F) in the genotype groups CYP2C9*1/*1, *1/*2, *1/*3, *2/*3, and *3/*3 before rifampin were 0.78, 0.74, 0.52, 0.40, and 0.13 l/h, respectively. After rifampin administration, these clearances increased in all genotype groups by a median factor of 1.9 (range 1.1-4.8). The combined effects of genes and environment could be predicted by a simple additive model. Thus, enzyme induction resulted in an approximately twofold difference in CYP2C9 activity, irrespective of the CYP2C9 genotypes. But the difference in activity levels between the CYP2C9*1/*1 and *3/*3 genotypes before the administration of rifampin was sixfold.